The successful use of artificial intelligence (AI) for diagnostic purposes has prompted the
application of AI-based cancer imaging analysis to address other, more complex, clinical …

Medical imaging can assess the tumor and its environment in their entirety, which makes it
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …

Background & Aims Microvascular invasion (MVI) impairs surgical outcomes in patients with
hepatocellular carcinoma (HCC). As there is no single highly reliable factor to preoperatively …

Radiomics, the high-throughput mining of quantitative image features from standard-of-care
medical imaging that enables data to be extracted and applied within clinical-decision …

Traditional radiomics models mainly rely on explicitly-designed handcrafted features from
medical images. This paper aimed to investigate if deep features extracted via transfer …

The current tumour-node-metastasis (TNM) staging system alone cannot provide adequate
information for prognosis and adjuvant chemotherapy benefits in patients with gastric cancer …

Lung cancer is responsible for a large proportion of cancer-related deaths across the globe,
with delayed detection being perhaps the most significant factor for its high mortality rate …

Purpose: We aimed to evaluate the value of deep learning on positron emission tomography
with computed tomography (PET/CT)–based radiomics for individual induction …

Purpose: To identify MRI-based radiomics as prognostic factors in patients with advanced
nasopharyngeal carcinoma (NPC). Experimental Design: One-hundred and eighteen …

Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male
population. The diagnosis, the identification of aggressive disease, and the post-treatment …